AITCare-Vision predicts cognitive decline by analyzing sleep-wake disorders data in older adults. Using computer vision and motion sensors coupled with AI algorithms, AITCare-Vision continuously monitors sleep patterns, including disturbances such as frequent nighttime awakenings or irregular sleep cycles. AITCare-Vision utilizes this data to identify patterns that may signal cognitive decline, such as changes in sleep consistency or increased time spent awake at night. These insights are compared with baseline data to detect subtle shifts in cognitive health over time. In this presentation we’ll discuss the development of AITCare-Vision. We’ll focus on some of the key challenges we addressed in the development process, including devising techniques to obtain accurate sleep-wake data without the use of wearables, designing the system to preserve privacy and implementing techniques to enable running AI models at the edge with low power consumption.